Category Archives: Robotic Software

Massive parallelization of POMDPs with a very good state-of-the-art review

Taekhee Lee, Young J. Kim (2015), Massively parallel motion planning algorithms under uncertainty using POMDP , The International Journal of Robotics Research, Vol 35, Issue 8, pp. 928 – 942, DOI: 10.1177/0278364915594856.

We present new parallel algorithms that solve continuous-state partially observable Markov decision process (POMDP) problems using the GPU (gPOMDP) and a hybrid of the GPU and CPU (hPOMDP). We choose the Monte Carlo value iteration (MCVI) method as our base algorithm and parallelize this algorithm using the multi-level parallel formulation of MCVI. For each parallel level, we propose efficient algorithms to utilize the massive data parallelism available on modern GPUs. Our GPU-based method uses the two workload distribution techniques, compute/data interleaving and workload balancing, in order to obtain the maximum parallel performance at the highest level. Here we also present a CPU–GPU hybrid method that takes advantage of both CPU and GPU parallelism in order to solve highly complex POMDP planning problems. The CPU is responsible for data preparation, while the GPU performs Monte Cacrlo simulations; these operations are performed concurrently using the compute/data overlap technique between the CPU and GPU. To the best of the authors’ knowledge, our algorithms are the first parallel algorithms that efficiently execute POMDP in a massively parallel fashion utilizing the GPU or a hybrid of the GPU and CPU. Our algorithms outperform the existing CPU-based algorithm by a factor of 75–99 based on the chosen benchmark.

Model checking for the verification of the correct functionality in the presence of sensor failures of a network of behaviours included in a robotic architecture

Lisa Kiekbusch, Christopher Armbrust, Karsten Berns, Formal verification of behaviour networks including sensor failures, Robotics and Autonomous Systems, Volume 74, Part B, December 2015, Pages 331-339, ISSN 0921-8890, DOI: 10.1016/j.robot.2015.08.002.

The paper deals with the problem of verifying behaviour-based control systems. Although failures in sensor hardware and software can have strong influences on the robot’s operation, they are often neglected in the verification process. Instead, perfect sensing is assumed. Therefore, this paper provides an approach for modelling the sensor chain in a formal way and connecting it to the formal model of the control system. The resulting model can be verified using model checking techniques, which is shown on the examples of the control systems of an autonomous indoor robot and an autonomous off-road robot.

Survey on Model-Driven Software Engineering for real-time embedded systems and robotics

Brugali, D., Model-Driven Software Engineering in Robotics: Models Are Designed to Use the Relevant Things, Thereby Reducing the Complexity and Cost in the Field of Robotics, in Robotics & Automation Magazine, IEEE , vol.22, no.3, pp.155-166, Sept. 2015, DOI: 10.1109/MRA.2015.2452201.

A model is an abstract representation of a real system or phenomenon [1]. The idea of a model is to capture important properties of reality and to eglect irrelevant details. The properties that are relevant and that can be neglected depend on the purpose of creating a model. A model can make a particular system or phenomenon easier to understand, quantify, visualize, simulate, or predict.

Checking the behavior of robotic software (i.e., verification) and embedded sw in general, with a good related work on the issue

Lyons, D.M.; Arkin, R.C.; Shu Jiang; Tsung-Ming Liu; Nirmal, P., Performance Verification for Behavior-Based Robot Missions, Robotics, IEEE Transactions on , vol.31, no.3, pp.619,636, June 2015, DOI: 10.1109/TRO.2015.2418592.

Certain robot missions need to perform predictably in a physical environment that may have significant uncertainty. One approach is to leverage automatic software verification techniques to establish a performance guarantee. The addition of an environment model and uncertainty in both program and environment, however, means that the state space of a model-checking solution to the problem can be prohibitively large. An approach based on behavior-based controllers in a process-algebra framework that avoids state-space combinatorics is presented here. In this approach, verification of the robot program in the uncertain environment is reduced to a filtering problem for a Bayesian network. Validation results are presented for the verification of a multiple-waypoint and an autonomous exploration robot mission.

Interesting paper on fault tolerance applied to robotics, with good survey of the subject

D. Crestani, K. Godary-Dejean, L. Lapierre, Enhancing fault tolerance of autonomous mobile robots, Robotics and Autonomous Systems, Volume 68, June 2015, Pages 140-155, ISSN 0921-8890, DOI: 10.1016/j.robot.2014.12.015.

Experience demonstrates that autonomous mobile robots running in the field in a dynamic environment often breakdown. Generally, mobile robots are not designed to efficiently manage faulty or unforeseen situations. Even if some research studies exist, there is a lack of a global approach that really integrates dependability and particularly fault tolerance into the mobile robot design.
This paper presents an approach that aims to integrate fault tolerance principles into the design of a robot real-time control architecture. A failure mode analysis is firstly conducted to identify and characterize the most relevant faults. Then the fault detection and diagnosis mechanisms are explained. Fault detection is based on dedicated software components scanning faulty behaviors. Diagnosis is based on the residual principle and signature analysis to identify faulty software or hardware components and faulty behaviors. Finally, the recovery mechanism, based on the modality principle, proposes to adapt the robot’s control loop according to the context and current operational functions of the robot.
This approach has been applied and implemented in the control architecture of a Pioneer 3DX mobile robot.

Abstract data-type for exchanging information in real-time systems, prioritizing the access to newest data rather than to oldest

Dantam, N.T.; Lofaro, D.M.; Hereid, A.; Oh, P.Y.; Ames, A.D.; Stilman, M., The Ach Library: A New Framework for Real-Time Communication, Robotics & Automation Magazine, IEEE , vol.22, no.1, pp.76,85, March 2015, DOI: 10.1109/MRA.2014.2356937.

Correct real-time software is vital for robots in safety-critical roles such as service and disaster response. These systems depend on software for locomotion, navigation, manipulation, and even seemingly innocuous tasks such as safely regulating battery voltage. A multiprocess software design increases robustness by isolating errors to a single process, allowing the rest of the system to continue operation. This approach also assists with modularity and concurrency. For real-time tasks, such as dynamic balance and force control of manipulators, it is critical to communicate the latest data sample with minimum latency. There are many communication approaches intended for both general-purpose and real-time needs [9], [13], [15], [17], [19]. Typical methods focus on reliable communication or network transparency and accept a tradeoff of increased message latency or the potential to discard newer data. By focusing instead on the specific case of real-time communication on a single host, we reduce communication latency and guarantee access to the latest sample. We present a new interprocess communication (IPC) library, Ach which addresses this need, and discuss its application for real-time multiprocess control on three humanoid robots (Figure 1). (Ach is available at http://www.golems.org/projects/ach.html. The name Ach comes from the common abbreviation for the motor neurotransmitter Acetylcholine and the computer networking term ACK.).